Economic and Environmental Considerations in a Stochastic Inventory Control Model with Order Splitting under Different Delivery Schedules among Suppliers
Economic and Environmental Considerations in a Stochastic Inventory Control Model with Order Splitting under Different Delivery Schedules among Suppliers
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DOI：
10.1016/j.omega.2016.08.013
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发表时间：
2017-09
影响因子：
6.9
通讯作者：
D. Konur;James F. Campbell;Sepideh Almasi Monfared
中科院分区：
文献类型：
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作者：
D. Konur;James F. Campbell;Sepideh Almasi Monfared
本研究分析一随机需求环境下之整合库存控制与运送排程问题，并考虑经济与环境因素。特别是，我们研究了一个双目标的连续审查库存控制模型与多个供应商之间的订单分割，在期望成本和单位时间的碳排放量最小化。针对该问题，考虑了两种不同的订单分割调度策略：顺序分割和顺序交货。首先，我们制定的问题下的每一个交付调度政策的双目标混合整数非线性模型。然后，提出了一种自适应约束算法和进化搜索算法来逼近这些模型的Pareto前沿。数值研究进行了比较这两种近似算法。另一个数值研究表明，在每一个交付调度政策的期望成本和单位时间的碳排放量的需求方差的影响。最后，举例说明如何在这项研究中提供的工具可以用来比较不同的调度策略。我们的研究结果表明，交付政策和供应商的选择都有很强的经济和环境绩效的影响，也是一个很好的近似帕累托前沿是至关重要的准确比较交付调度政策。
This study analyzes an integrated inventory control and delivery scheduling problem in a stochastic demand environment with economic and environmental considerations. In particular, we examine a bi-objective continuous review inventory control model with order splitting among multiple suppliers, where both expected costs and carbon emissions per unit time are minimized. For this problem, two different delivery scheduling policies are considered for the split orders: sequential splitting and sequential delivery. First, we formulate the problem under each delivery scheduling policy as bi-objective mixed-integer nonlinear models. Then, an adaptiveϵ-constraint algorithm and an evolutionary search algorithm are proposed to approximate the Pareto front of these models. A numerical study is conducted to compare the two approximation algorithms. Another numerical study demonstrates the effects of the demand variance on the expected costs and carbon emissions per unit time under each delivery scheduling policy. Finally, examples are presented to show how the tools provided in this study can be used to compare different scheduling policies. Our results show that the delivery policy and supplier selection both have strong effects on the economic and environmental performance, and also that a good approximation of the Pareto front is crucial to accurately compare delivery scheduling policies.